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https://hdl.handle.net/1959.11/26246

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DC Field

Value

Language

dc.contributor.author

Charlesworth, Richard P G

en

dc.contributor.author

Agnew, Linda L

en

dc.contributor.author

Scott, David R

en

dc.contributor.author

Andronicos, Nicholas M

en

dc.date.accessioned

2019-01-10T01:28:50Z

-

dc.date.available

2019-01-10T01:28:50Z

-

dc.identifier.citation

Journal of Gastroenterology and Hepatology, p. 1-9

en

dc.identifier.issn

0815-9319

en

dc.identifier.issn

1440-1746

en

dc.description.abstract

Background and Aim: The diagnosis of celiac disease autoimmune pathology relies on the subjective histological assignment of biopsies into Marsh score categories. It is hypothesized that Marsh score categories have unique gene expression signatures. The aims were as follows: first, to develop a celiac disease quantitative reverse transcription–polymerase chain reaction (RT-PCR) array; second, define gene expression signatures associated with Marsh score categories; and third, develop equations that classify biopsies into Marsh score categories and to monitor the efficacy of patient treatment. Methods: Gene targets for inclusion in the celiac RT-PCR (qRT-PCR) array were identified using systematic analysis of published celiac transcriptomic data. The array was used to assess the gene expression associated with histological changes in duodenal biopsies obtained from adult patients. Finally, Marsh score classification equations were defined using discriminant analysis. Results: The array contained 87 genes. The expression of 26 genes were significantly (p < 0.06) associated with the discrete Marsh score categories. As the Marsh score pathology of biopsies increased, there was a progression of innate immune gene expression through adaptive Th1-specific gene expression with a concurrent decrease in intestinal structural gene expression in high Marsh score samples. These 26 genes were used to define classification equations that accounted for 99% of the observed experimental variation and which could classify biopsies into Marsh score categories and monitor patient treatment progression. Conclusions: This proof-of-concept study successfully developed a celiac RT-PCR array and has provided evidence that discriminant equations defined using gene expression data can objectively and accurately classify duodenal biopsies into Marsh score categories.

en

dc.language

en

en

dc.publisher

Wiley-Blackwell Publisher Asia

en

dc.relation.ispartof

Journal of Gastroenterology and Hepatology

en

dc.title

Celiac disease gene expression data can be used to classify biopsies along the Marsh score severity scale

en

dc.type

Journal Article

en

dc.identifier.doi

10.1111/jgh.14369

en

dc.subject.keywords

Autoimmunity

en

dc.subject.keywords

Pathology (excl. Oral Pathology)

en

dc.subject.keywords

Medical Biotechnology Diagnostics (incl. Biosensors)

en

local.contributor.firstname

Richard P G

en

local.contributor.firstname

Linda L

en

local.contributor.firstname

David R

en

local.contributor.firstname

Nicholas M

en

local.subject.for2008

100402 Medical Biotechnology Diagnostics (incl. Biosensors)

en

local.subject.for2008

110316 Pathology (excl. Oral Pathology)

en

local.subject.for2008

110703 Autoimmunity

en

local.subject.seo2008

920105 Digestive System Disorders

en

local.subject.seo2008

920108 Immune System and Allergy

en

local.profile.school

School of Science and Technology

en

local.profile.school

School of Science and Technology

en

local.profile.school

School of Science and Technology

en

local.profile.email

rcharle3@une.edu.au

en

local.profile.email

lagnew2@une.edu.au

en

local.profile.email

dscott39@myune.edu.au

en

local.profile.email

nandroni@une.edu.au

en

local.output.category

C1

en

local.record.place

au

en

local.record.institution

University of New England

en

local.publisher.place

Australia

en

local.format.startpage

1

en

local.format.endpage

9

en

local.peerreviewed

Yes

en

local.contributor.lastname

Charlesworth

en

local.contributor.lastname

Agnew

en

local.contributor.lastname

Scott

en

local.contributor.lastname

Andronicos

en

dc.identifier.staff

une-id:rcharle3

en

dc.identifier.staff

une-id:lagnew2

en

dc.identifier.staff

une-id:dscott39

en

dc.identifier.staff

une-id:nandroni

en

local.profile.orcid

0000-0002-2803-0995

en

local.profile.orcid

0000-0001-5881-2296

en

local.profile.role

author

en

local.profile.role

author

en

local.profile.role

author

en

local.profile.role

author

en

local.identifier.unepublicationid

une:-20180831-091220

en

local.identifier.unepublicationid

une:-20180831-091220

en

local.date.onlineversion

2018-07-02

en

dc.identifier.academiclevel

Academic

en

dc.identifier.academiclevel

Academic

en

dc.identifier.academiclevel

Academic

en

dc.identifier.academiclevel

Academic

en

local.title.maintitle

Celiac disease gene expression data can be used to classify biopsies along the Marsh score severity scale

The University of New England respects and acknowledges that its people, programs and facilities are built on land, and surrounded by a sense of belonging, both ancient and contemporary, of the world's oldest living culture. In doing so, UNE values and respects Indigenous knowledge systems as a vital part of the knowledge capital of Australia.